clarify

name	clarify
description	Lightweight spec clarification scan for jig projects — a six-category ambiguity audit that asks up to five prioritized questions and appends them to the spec's `## Clarifications` section. Auto-triggers when you say clarify this spec, audit this spec for ambiguities, is this spec ready for review, find unknowns in this scope, surface what's still unclear or unspecified, scan for unanswered questions, or what's missing from this spec. Do not use for: spec-compliance review of a finished slice (use `/jig:independent-review` instead); cross-artifact consistency analysis or drift detection (use `/jig:analyze` instead); project-vision or architecture elicitation (use `/jig:vision-elicitation` instead).
user-invocable	true

Spec 023 introduces this skill as jig's pre-spec ambiguity scan. It is the sixth non-stub active jig skill that ships without a .py helper — clarify is fundamentally a judgment skill, and the determinism it needs (locate the target doc, find an existing ## Clarifications section if any, append new entries) Claude can run inline via Read + Edit. The skill slots between workflow.py new <slug> (stub reservation) and the READY_FOR_REVIEW transition (spec body ready for first review).

Per user direction on 2026-05-18, jig's clarify ships as a standalone baseline, not a deferral surface. Power users who want spec-kit's /speckit.clarify install spec-kit and invoke it explicitly under /speckit.*. There is no category-based deferral hint in this skill's description.

What this skill does

Runs a structured ambiguity scan against a DRAFT-state spec document across six categories aligned with jig's slice template (Scope & Boundaries / Acceptance Criteria Testability / Dependencies & Blockers / Non-functional Requirements / Edge Cases & Failure Modes / Terminology Consistency). The skill rates each category Clear / Partial / Missing, selects up to five prioritized questions (Partial/Missing weighted above Clear), asks them one at a time recording the user's verbatim answer, and appends a ## Clarifications section to the target document with the Q/A entries plus a coverage summary table.

The skill is breadth over depth: catch the obvious unanswered questions across the six taxonomy categories in a few minutes, leave deep domain-specific clarification (legal review, regulatory edges, multi-stakeholder facilitation) to the dev's judgment or to a richer team process. The five-question budget exists to keep the scan lightweight enough to actually run before each READY_FOR_REVIEW transition — not so heavy it becomes a chore the team skips.

When to use vs. when to defer

There are four sibling skills people often confuse with this one. Pick the right one:

• /jig:spec-workflow — sibling skill for state transitions (workflow.py new, workflow.py transition, status board regen). Spec-workflow moves a slice between DRAFT / READY_FOR_REVIEW / IN_PROGRESS / REVIEWED / RECONCILED / DONE; it does not elicit clarifications. Reach for /jig:spec-workflow when you want to reserve a new spec number or push a slice to the next state. Reach for this skill when the spec body has gaps you want surfaced before the next transition.
• /jig:analyze — sibling jig skill (spec 024, sequenced after this one) for cross-artifact consistency analysis. Analyze reads multiple specs + ADRs + docs and surfaces drift between them. This skill scans one document for internal ambiguities. Reach for /jig:analyze when you suspect a spec disagrees with another spec or with an ADR. Reach for this skill when one spec's body has unanswered questions in isolation.
• /jig:vision-elicitation — sibling skill that fills slots in docs/product-vision.md and docs/architecture.md. That's project-scope elicitation: who are the users, what's the problem, what's the architecture? This skill is spec-scope elicitation: what does this one slice mean, what are its ACs, what are its dependencies? Reach for vision-elicitation immediately after scaffold-init; reach for this skill when authoring or reviewing a single spec.
• /jig:independent-review — sibling skill that reviews a finished slice against its spec.md. Independent-review assumes the spec is clear — it checks the implementation against the ACs. This skill helps make the spec clear in the first place, so independent-review has something specific to review against. Reach for /jig:independent-review after the slice is implemented; reach for this skill before the slice has transitioned to READY_FOR_REVIEW.

Rule of thumb: draft a spec → this skill. Transition a spec → /jig:spec-workflow. Audit across specs → /jig:analyze. Review the implementation → /jig:independent-review. Set up the project → /jig:vision-elicitation.

Inputs

Two input modes, both supported by the MVP:

1. Single spec.md (overview-level scan). The user names a spec directory (docs/specs/023-clarify/) or its spec.md file directly. The scan covers the spec body's Overview / Why now / Goals / Non-goals / Decomposition / Open questions sections. The ## Clarifications section gets appended to that spec.md.
2. One slice-NN-*.md (slice-level scan). The user names a specific slice file (docs/specs/023-clarify/slice-01-clarify-skill-md.md). The scan covers the slice's Goal / DoR / Acceptance Criteria / DoD / Anti-horizontal-phasing check. The ## Clarifications section gets appended to that slice file (not to the parent spec.md).

Mixed-mode ("scan the spec AND every slice") is explicitly NOT supported by the MVP. That requires per-doc bookkeeping and a re-entry/resume protocol that's out of scope for this slice. If the same friction surfaces three times across real usage, a future slice 023-02 can ship a .py helper that orchestrates the loop. Until then, the user re-runs the skill per document.

Six-category taxonomy

For each category, the skill rates the target document Clear / Partial / Missing. The scan is internal to the model — the rating is not shown to the user unless an answer is sought. The categories below are aligned with jig's slice template; spec-kit's nine-category taxonomy was slimmed to six by dropping "Domain & Data Model" and "Interaction & UX Flow" (which assume slots jig's slice template doesn't have) and folding their substance into "Scope & Boundaries" where it applies.

Scope & Boundaries

What is in-scope, what is out-of-scope, what is the boundary with adjacent specs? Watch for unstated assumptions about which layer or module the change touches.

What to check:

• Is the in-scope deliverable named in concrete terms (file paths, function names, observable outcomes)?
• Are non-goals enumerated? Or is the spec silent on what it explicitly won't do?
• Is the boundary with adjacent specs declared? E.g. "spec 022 covers external surfaces; this spec is internal-only."
• For multi-slice specs: does each slice's scope fit on its own without the parent overview?

Acceptance Criteria Testability

Can each AC be turned into a passing test or a measurable observation from outside the helper? Watch for vague verbs ("works correctly", "handles edge cases") that hide unspecified behavior.

What to check:

• Does each AC name a measurable outcome (a file exists, a function returns X, an exit code is N)?
• Is each AC observable from outside the helper — testable without inspecting private state?
• Is the AC count reasonable for one slice (~3-10)? Too few suggests under-specification; too many suggests a horizontal phasing problem.
• Are ACs phrased imperatively ("the helper exits 0 on success") rather than aspirationally ("the helper should work well")?

Dependencies & Blockers

What must be true before this slice can land? Watch for upstream work that's silently assumed.

What to check:

• Are upstream slices listed in dependencies: frontmatter? Are they all DONE?
• Are referenced ADRs accepted (not still DRAFT)?
• Are external services / fixtures / sample data available?
• Are reviewer-side prerequisites named (e.g. "reviewer needs access to spec-kit reference text")?

Non-functional Requirements

Performance / security / observability / backwards-compat / accessibility / regulatory constraints. Watch for the case where the spec body assumes "normal" but never declares what abnormal looks like.

What to check:

• Are performance constraints named (latency budget, payload size limits)?
• Are security expectations named (auth required, secrets handling, PII boundaries)?
• Is observability declared (logs / metrics / events emitted)?
• Is the backwards-compat policy stated (semver bump? feature flag? silent migration?)?

Edge Cases & Failure Modes

What can go wrong? What does the spec say about each failure path? Watch for the happy path being the only path drawn.

What to check:

• Are explicit refusals enumerated (the helper exits N on condition X)?
• Are failure paths drawn — what the user sees when something goes wrong?
• Are race conditions / partial-state failures considered (e.g. file written but commit refused)?
• Is the empty-input case named (no slices yet, no ADRs yet, empty spec directory)?

Terminology Consistency

Are domain terms used consistently? Watch for the same concept appearing under two names, or two concepts collapsing under one name.

What to check:

• Are glossary terms used consistently with docs/memory/glossary.md?
• Do "slice" and "task" / "spec" and "issue" / "ADR" and "decision" mean exactly one thing each in this doc?
• Are skill names spelled the same throughout (/jig:slice-land vs slice-land vs "the land helper")?
• Are tier labels consistent (Tier 0 vs tier-0 vs "always-on")?

Question-asking loop

The algorithm has four phases:

1. Internal coverage scan. The skill reads the target document and rates each of the six categories Clear / Partial / Missing. This rating is not shown to the user.
2. Prioritized question selection. The skill picks up to five questions to ask, weighted Partial > Missing > Clear. (Clear categories almost never yield useful questions; Partial means "the spec touches this but the answer is ambiguous"; Missing means "the category isn't addressed at all".) The five-question budget is hard: even if the spec has eight gaps, the skill asks five and stops.
3. Sequential Q&A. The skill asks one question at a time. After each answer, it records the user's verbatim words and moves to the next question. The user can answer, skip, or say "stop / skip remaining" to short-circuit.
4. Stop conditions. The loop ends when any of:
   • Five questions have been asked.
   • All six categories are now Clear or Skipped.
   • The user types "stop" or "skip remaining".
   • The user closes the session.

After the loop, the skill renders the Q&A entries and the coverage summary table as a ## Clarifications section appended to the target document.

Question phrasing

Questions are concrete, single-axis, and answerable in 1-3 sentences. Bad: "What about edge cases?" (vague). Good: "What happens if the target directory already contains a .claude/ folder with no scaffold.json — refuse, merge, or overwrite?" (concrete, three named options, answerable directly).

When the model can offer a recommended default, it does — but the user's verbatim answer is what gets written, not the default.

Output: the ## Clarifications section

After the Q&A loop, the skill appends a ## Clarifications section to the target document. The exact shape:

## Clarifications

### Q1: <verbatim question>
_(category: <category-name>)_
_(provenance: [grounded: ADR-NNNN | path/to/doc] or [judgment])_

<verbatim user answer>

### Q2: <verbatim question>
_(category: <category-name>)_
_(provenance: [grounded: ADR-NNNN | path/to/doc] or [judgment])_

<verbatim user answer>

...

### Coverage summary

| Category | Status |
|---|---|
| Scope & Boundaries | Clear / Partial / Resolved / Outstanding / Skipped |
| Acceptance Criteria Testability | ... |
| Dependencies & Blockers | ... |
| Non-functional Requirements | ... |
| Edge Cases & Failure Modes | ... |
| Terminology Consistency | ... |

Status taxonomy in the coverage summary table:

• Clear — category was Clear before the scan; no question asked.
• Resolved — category was Partial or Missing; a question was asked and answered, closing the gap.
• Partial — category is partly clear after the scan; some questions remain unanswered (e.g. the five-question budget was hit before this category was reached).
• Outstanding — category is still Missing; a question was asked but the user deferred, or no question was reached.
• Skipped — the user explicitly skipped the question or the category.

Provenance tag (measurement, non-gating). Before writing each answered question, self-assess whether it could have been answered from an existing artifact already in the repo: [grounded: ADR-NNNN | path] when the answer restates (or was clearly derivable from) a named ADR or doc you could have read first, [judgment] when it's a genuine trade-off call that needed the user's input. Best-effort and non-blocking — it exists so a future rollup can measure whether clarify is asking already-answerable questions before building a grounding pass (docs/refinement-todo.md "Instrument the review→learnings→clarify loop before building it").

Append-only behavior. The skill does not modify any existing section in the spec body above the ## Clarifications heading. If ## Clarifications already exists (re-run case), the new entries append to the existing section rather than starting a new one. Q numbers continue from the highest existing number — Q4 becomes Q5, Q5 becomes Q6, etc.

Gotchas

• Verbatim-answer rule. The skill does not paraphrase, expand, or "improve" the user's answers. If the user says "refuse if .claude already exists," that's what gets written — not "the helper SHALL reject the operation when a .claude/ directory is present in the target." Same boundary as /jig:vision-elicitation: the user's voice in the final doc is what matters. Only two narrow exceptions: (a) markdown structure (rendering a list as a bullet list), (b) preserving the user's stated order (if Q3 lists three options in priority order, write them in that order).
• Advisory, not a state-machine gate. workflow.py transition DRAFT → READY_FOR_REVIEW does not refuse the transition if ## Clarifications is absent. Clarify is recommended, not enforced. Same shape as /jig:pr-review: calling it is a workflow choice, not a step jig blocks on.
• One-doc-at-a-time scope. The MVP scans one document per invocation. Either the spec.md (overview-level) or one slice-NN-*.md (slice-level), never both. If the same friction surfaces three times across real usage, slice 023-02 can ship a helper that orchestrates the loop. Until then, re-run the skill per document.
• No .py helper. All section surgery via Read + Edit. The skill reads the target document inline, scans the body, asks questions, and appends the ## Clarifications section by writing the rendered markdown via the Edit tool. No subprocess; no helper to invoke separately. The trade-off: the Q/A loop is conversational rather than batch-driven, and section detection is by visible H2 heading rather than by frontmatter marker.
• Re-runs append, not replace. A second invocation against a doc that already has ## Clarifications extends the existing section. Old Q/A entries stay; new Q/A entries follow with continuing Q numbers. The Coverage summary table is rewritten to reflect the union of both passes (a category that was Outstanding after pass 1 and Resolved after pass 2 reads Resolved).
• Five-question budget is a hard ceiling, not a target. If the scan finds three gaps and the user answers them all in three questions, the skill stops at three. Don't pad the loop to five if the scan converges sooner.

Relationship to other skills

• /jig:spec-workflow — sibling, different shape. Spec-workflow drives state transitions; this skill helps make a DRAFT spec ready for the first review-state transition. Two skills compose: this skill clarifies the spec body, spec-workflow transitions the slice forward.
• /jig:analyze — sibling (spec 024, sequenced after this spec). Analyze reads multiple specs + ADRs + docs and surfaces drift between them. This skill scans one document. Different scope, complementary purpose: clarify before READY_FOR_REVIEW, analyze after IN_PROGRESS to catch cross-artifact regressions.
• /jig:vision-elicitation — sibling, different scope. Vision- elicitation fills project-level slots in product-vision.md and architecture.md; this skill clarifies spec-level slots in a single spec.md or slice file. The two skills don't overlap.
• /jig:independent-review — sibling, downstream. Independent- review reviews a finished implementation against a written spec; this skill helps write a spec the reviewer can evaluate against. Without clarify, ambiguous ACs lead to reviewer findings that are really spec-clarity findings.
• /jig:adr-workflow — orthogonal. If a clarification answer amounts to a permanent decision ("we will use Python 3 stdlib only; no pip dependencies"), the user should also run /jig:adr-workflow new to capture the decision in an ADR. The ## Clarifications entry shows the moment of resolution; the ADR is the durable record.